With the development of technological devices, input interface methods have been developed to accept input in various forms, such as a touch, a gesture, writing recognition, voice recognition, and so on. Most new input methods for terminals are based on recognition technology. In the case of the writing recognition, the voice recognition, or the like, recognition technology for recognizing a language is needed, and thus a recognition device may need a linguistic model-based process.
A structure of a linguistic recognition device varies depending on the relevant recognition technology.
FIG. 1 is a schematic view showing a linguistic recognition device according to the related art.
Referring to FIG. 1, the writing recognition language-based system 10 of the related art may operate as follows. First, handwriting pixel information from a writing input image, handwriting information based on a writing order, or the like, are obtained and then a character is recognized through a writing recognition engine 16 and a handwriting model database 12. Then, a word or a sentence is inferred by comparing the recognized character with a word or a sentence from a stored common linguistic model database 14. Next, a recognition result is determined from results recognized in a unit of a character or in a unit of a word or sentence.
In the word or sentence recognition, recognized characters linguistically constitute a word or a sentence, and results misrecognized in the unit of the character are corrected by comparison with similar words or sentences. The recognition engine needs a word database based on the linguistic model for a word recognition unit. In the case of a standalone recognition engine, a common linguistic model database 14 for storing general information for the recognition linguistic model is embedded in the recognition engine by taking general users into account. The common linguistic model data is optimized to accommodate many general users and thus updated over a significantly long period. Also, a training tool may be provided in accordance with the recognition engine. However, in this case a user has to train the engine, for example, by inputting a word to be trained, and other related processes.
Since the linguistic model database of the recognition engine is optimized to accommodate a general group of users, word recognition inference results may cause deterioration in recognition performance with regard to words (e.g., an abbreviation, etc.), to slang, to tone of voice, or the like, characteristically used by individuals, with regard to newly-coined words, informal terms, vulgar words, or the like, with regard to a person, a place name, or similar proper noun following a trend, or with regard to technical terms, informal terms, or the like, restrictively used in a group to which users belong (e.g., an age group, a school, a hobby society, or the like).
Therefore, a need exists for a device, a method and a system for providing a linguistic model database which improves the precision of linguistic model probability inference in linguistic recognition.
The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.